DESCRIPTIVE STATISTICS IN ECOLOGICAL MONITORING
Abstract
This article discusses the impact of suspended particles on human health, as well as the analysis of the level ofpollution in Almaty over the past 2 years using descriptive statistics. Pollution of the environment by industrial enterprises and vehicles, causing degradation of the environment and causing damage to public health, remains the most acute environmental problem ofpriority social and economic importance. The problem of pollution of the environment of large cities is very significant and complex, requiring first of all long-term monitoring, then a deep and competent analysis of the assessment of the situation on the data obtained, for the subsequent prevention, localization and investigation of environmental disasters and incidents, making management decisions for further work on the development of improving the quality of atmospheric air, as well as forecasting the state of the environment. In this paper, we consider a specific case, namely particles PM 2.5 — air pollutant, which consists of solid particles and liquid droplets ranging in size from 10 nm to 2.5 microns. The fact that air pollution by small particles is a global killer is already widely known, but these statements have not yet been confirmed by specific figures. The authors have identified certain patterns, such as dependence on the time ofyear, weather, and the location of certain industrial facilities near the observed zone. The indicators with the values in the form of graphs And revealed that the concentration of suspended particles in the air exceeds the norm by 2 times most of the observed period of time, and considered the possible consequences of this.
About the Authors
Zh. N. SarsenovaKazakhstan
V. T. Pyagai
Kazakhstan
Z. Ye. Tuyakova
Kazakhstan
References
1. Chung, Y., Dominici, F., Wang, Y, Coull, B. and Bell, M. (2015). Associations between Long Term Exposure to Chemical Constituents of Fine Particulate Matter (PM 2.5 ) and Mortality in Medicare Enrollees in the Eastern United States. Environmental Health Perspectives, 123(5), pp.467-474.
2. William M. Hodan, and William R. Barnard, (n.d.). Evaluating the Contribution of PM2.5 Precursor Gases and Re-entrained Road Emissions to Mobile Source PM2.5 Particulate Matter Emissions.
3. Phipps, J., Aronoff, D., Curtis, J., Goel, D., O’Brien, E. and Mancuso, P. (2010). Cigarette Smoke Exposure Impairs Pulmonary Bacterial Clearance and Alveolar Macrophage Complement-Mediated Phagocytosis of Streptococcus pneumoniae. Infection and Immunity, 78(3), pp.1214-1220.
4. Orru, H., Maasikmets, M., Lai, T., Tamm, T., Kaasik, M., Kimmel, V, Orru, K., Merisalu, E. and Forsberg, B. (2011). Health impacts of particulate matter in five major Estonian towns: main sources of exposure and local differences. Air Quality, Atmosphere & Health, 4(3-4), pp.247-258.
5. Grigorieva I. A., Subsystem of analysis of data and machine training for information and analytical system ecohealth [Podsistema analiza dannikh I mashinnogo obucheniya dlya informatsionno-analiticheskoy sistemy ecohealth]. (2017). Student, [online] 5 (5), pp.40-46. Available at: https://sibac.info/journal/student/5/75629.
6. AirPaca. (2019). Association de surveillance de la qualite de l ’air agreeepar le ministere de l ’environnement. . [online] Available at: https://keep.eu/partners/33727/Air-PACAEN/ [Accessed 23 Apr. 2019].
7. En.wikipedia.org. (2019). Johnson’ s SU-distribution. [online] Available at: https://en.wikipedia.org/wiki/Johnson%27s_SU-distribution [Accessed 23 Apr. 2019].
Review
For citations:
Sarsenova Zh.N., Pyagai V.T., Tuyakova Z.Ye. DESCRIPTIVE STATISTICS IN ECOLOGICAL MONITORING. Herald of the Kazakh-British technical university. 2019;16(3):292-300.